Extended results

Study 1

Exploratory factor analyses (EFAs)

Parallel analysis

## Parallel analysis suggests that the number of factors =  4  and the number of components =  3
## Loading required namespace: GPArotation
## Factor Analysis using method =  minres
## Call: fa(r = d1_all, nfactors = s1_parallel$nfact, rotate = "oblimin")
## Standardized loadings (pattern matrix) based upon correlation matrix
##                                                 MR1   MR3   MR2   MR4   h2   u2
## planning                                       1.01 -0.11 -0.01 -0.04 0.86 0.14
## having_self_control                            0.96 -0.02 -0.01 -0.05 0.86 0.14
## thinking_before_they_act                       0.96 -0.03  0.03 -0.04 0.85 0.15
## having_goals                                   0.95 -0.08  0.00  0.02 0.83 0.17
## reasoning_about_things                         0.94  0.00 -0.01 -0.05 0.84 0.16
## controlling_their_emotions                     0.92 -0.01 -0.02 -0.06 0.79 0.21
## telling_right_from_wrong                       0.91  0.00  0.03  0.01 0.86 0.14
## understanding_what_somebody_else_is_thinking   0.90 -0.05 -0.04  0.03 0.78 0.22
## focusing_on_a_goal                             0.90  0.02  0.00 -0.02 0.81 0.19
## feeling_guilty                                 0.89 -0.04  0.06  0.09 0.84 0.16
## feeling_embarrassed                            0.83  0.04  0.01  0.09 0.83 0.17
## feeling_pride                                  0.83  0.07 -0.05  0.09 0.83 0.17
## making_choices                                 0.69  0.32 -0.04 -0.02 0.82 0.18
## calming_themselves_down                        0.68  0.25 -0.01 -0.05 0.70 0.30
## detecting_danger                               0.67  0.07  0.10  0.12 0.68 0.32
## feeling_hopeless                               0.67  0.01  0.01  0.28 0.72 0.28
## remembering_things                             0.52  0.49  0.01 -0.10 0.77 0.23
## imagining_things                               0.51  0.42 -0.01  0.03 0.74 0.26
## recognizing_others_emotions                    0.50  0.41 -0.04  0.03 0.68 0.32
## feeling_worried                                0.42  0.24  0.05  0.35 0.75 0.25
## getting_hurt_feelings                          0.41  0.40  0.00  0.19 0.73 0.27
## having_wants_and_desires                       0.29  0.26  0.17  0.27 0.60 0.40
## feeling_excited                                0.00  0.85 -0.01  0.06 0.76 0.24
## finding_something_funny                        0.06  0.84 -0.02  0.00 0.75 0.25
## loving_somebody                                0.05  0.83 -0.10  0.09 0.73 0.27
## learning_from_other_people                     0.12  0.80 -0.02  0.01 0.76 0.24
## feeling_happy                                 -0.12  0.79  0.16  0.01 0.70 0.30
## feeling_loved                                 -0.05  0.77  0.04  0.07 0.65 0.35
## recognizing_somebody_else                      0.06  0.76  0.17 -0.10 0.73 0.27
## getting_pleasure_from_music                    0.10  0.62  0.17  0.04 0.66 0.34
## being_afraid_of_somebody                       0.02  0.62  0.11  0.26 0.74 0.26
## listening_to_somebody                          0.18  0.61  0.14 -0.03 0.64 0.36
## having_thoughts                                0.26  0.59  0.10  0.02 0.71 0.29
## feeling_sad                                    0.00  0.58  0.15  0.24 0.69 0.31
## feeling_safe                                   0.02  0.54  0.24  0.13 0.63 0.37
## feeling_textures_(for_example,_smooth,_rough)  0.06  0.54  0.36 -0.05 0.66 0.34
## getting_angry                                  0.09  0.53  0.05  0.34 0.72 0.28
## feeling_pleasure                               0.06  0.47  0.28  0.16 0.64 0.36
## being_angry_at_somebody                        0.38  0.42  0.00  0.25 0.79 0.21
## feeling_lonely                                 0.16  0.42  0.10  0.35 0.69 0.31
## feeling_bored                                  0.32  0.42  0.04  0.27 0.75 0.25
## feeling_confused                               0.16  0.41  0.10  0.36 0.71 0.29
## feeling_scared                                -0.06  0.41  0.37  0.27 0.69 0.31
## being_aware_of_things                          0.30  0.34  0.33  0.03 0.64 0.36
## getting_hungry                                -0.06 -0.13  0.90  0.01 0.69 0.31
## feeling_pain                                   0.00 -0.07  0.90  0.03 0.75 0.25
## feeling_tired                                  0.00 -0.06  0.88  0.02 0.72 0.28
## feeling_thirsty                                0.01  0.02  0.84 -0.04 0.72 0.28
## feeling_too_hot_or_too_cold                    0.03  0.09  0.77  0.02 0.72 0.28
## feeling_physically_uncomfortable               0.05 -0.02  0.76  0.18 0.71 0.29
## hearing_sounds                                -0.04  0.21  0.75 -0.13 0.69 0.31
## being_comforted_by_physical_touch             -0.03  0.17  0.72 -0.09 0.63 0.37
## feeling_distressed                             0.07  0.00  0.49  0.45 0.66 0.34
## seeing                                         0.01  0.46  0.47 -0.22 0.57 0.43
## feeling_calm                                   0.09  0.35  0.36  0.12 0.56 0.44
## feeling_helpless                               0.34  0.13  0.12  0.43 0.67 0.33
## feeling_overwhelmed                            0.22  0.25  0.12  0.42 0.65 0.35
## feeling_frustrated                             0.12  0.37  0.19  0.39 0.73 0.27
## feeling_annoyed                                0.24  0.37  0.07  0.38 0.75 0.25
## feeling_neglected                              0.16  0.26  0.25  0.36 0.64 0.36
##                                               com
## planning                                      1.0
## having_self_control                           1.0
## thinking_before_they_act                      1.0
## having_goals                                  1.0
## reasoning_about_things                        1.0
## controlling_their_emotions                    1.0
## telling_right_from_wrong                      1.0
## understanding_what_somebody_else_is_thinking  1.0
## focusing_on_a_goal                            1.0
## feeling_guilty                                1.0
## feeling_embarrassed                           1.0
## feeling_pride                                 1.0
## making_choices                                1.4
## calming_themselves_down                       1.3
## detecting_danger                              1.1
## feeling_hopeless                              1.3
## remembering_things                            2.1
## imagining_things                              1.9
## recognizing_others_emotions                   1.9
## feeling_worried                               2.6
## getting_hurt_feelings                         2.4
## having_wants_and_desires                      3.6
## feeling_excited                               1.0
## finding_something_funny                       1.0
## loving_somebody                               1.1
## learning_from_other_people                    1.0
## feeling_happy                                 1.1
## feeling_loved                                 1.0
## recognizing_somebody_else                     1.1
## getting_pleasure_from_music                   1.2
## being_afraid_of_somebody                      1.4
## listening_to_somebody                         1.3
## having_thoughts                               1.5
## feeling_sad                                   1.5
## feeling_safe                                  1.5
## feeling_textures_(for_example,_smooth,_rough) 1.8
## getting_angry                                 1.8
## feeling_pleasure                              1.9
## being_angry_at_somebody                       2.6
## feeling_lonely                                2.4
## feeling_bored                                 2.7
## feeling_confused                              2.4
## feeling_scared                                2.8
## being_aware_of_things                         3.0
## getting_hungry                                1.1
## feeling_pain                                  1.0
## feeling_tired                                 1.0
## feeling_thirsty                               1.0
## feeling_too_hot_or_too_cold                   1.0
## feeling_physically_uncomfortable              1.1
## hearing_sounds                                1.2
## being_comforted_by_physical_touch             1.2
## feeling_distressed                            2.0
## seeing                                        2.4
## feeling_calm                                  2.4
## feeling_helpless                              2.3
## feeling_overwhelmed                           2.4
## feeling_frustrated                            2.7
## feeling_annoyed                               2.7
## feeling_neglected                             3.2
## 
##                         MR1   MR3  MR2  MR4
## SS loadings           16.45 14.29 8.47 4.25
## Proportion Var         0.27  0.24 0.14 0.07
## Cumulative Var         0.27  0.51 0.65 0.72
## Proportion Explained   0.38  0.33 0.19 0.10
## Cumulative Proportion  0.38  0.71 0.90 1.00
## 
##  With factor correlations of 
##      MR1  MR3  MR2  MR4
## MR1 1.00 0.65 0.19 0.49
## MR3 0.65 1.00 0.59 0.50
## MR2 0.19 0.59 1.00 0.37
## MR4 0.49 0.50 0.37 1.00
## 
## Mean item complexity =  1.6
## Test of the hypothesis that 4 factors are sufficient.
## 
## The degrees of freedom for the null model are  1770  and the objective function was  73.6 with Chi Square of  64855.87
## The degrees of freedom for the model are 1536  and the objective function was  5.71 
## 
## The root mean square of the residuals (RMSR) is  0.02 
## The df corrected root mean square of the residuals is  0.02 
## 
## The harmonic number of observations is  903 with the empirical chi square  942.37  with prob <  1 
## The total number of observations was  903  with Likelihood Chi Square =  5012.16  with prob <  0 
## 
## Tucker Lewis Index of factoring reliability =  0.936
## RMSEA index =  0.05  and the 90 % confidence intervals are  0.049 0.052
## BIC =  -5441.43
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy             
##                                                    MR1  MR3  MR2  MR4
## Correlation of (regression) scores with factors   0.99 0.99 0.98 0.93
## Multiple R square of scores with factors          0.99 0.97 0.96 0.87
## Minimum correlation of possible factor scores     0.97 0.94 0.92 0.74
## Warning in if (is.na(factor_names)) {: the condition has length > 1 and only the
## first element will be used
## Joining, by = "capacity"
## Joining, by = "factor"
## Joining, by = "factor"
Factor loadings from an exploratory factor analysis of participants’ capacity attributions to newborns, 9-month-old infants, and 5-year-old children in Study 1.

Factor loadings from an exploratory factor analysis of participants’ capacity attributions to newborns, 9-month-old infants, and 5-year-old children in Study 1.

## Saving 4.5 x 5.4 in image
## Saving 4.5 x 5.4 in image

Minimizing BIC

## Warning in GPFoblq(L, Tmat = Tmat, normalize = normalize, eps = eps, maxit =
## maxit, : convergence not obtained in GPFoblq. 1000 iterations used.
## Factor Analysis using method =  minres
## Call: fa(r = d1_all, nfactors = s1_minbic$nfact, rotate = "oblimin")
## Standardized loadings (pattern matrix) based upon correlation matrix
##                                                 MR1   MR2   MR5   MR4   MR6
## being_afraid_of_somebody                       0.02  0.13  0.26  0.24  0.19
## being_angry_at_somebody                        0.37  0.05  0.10  0.16  0.10
## being_aware_of_things                          0.30  0.24 -0.02  0.23  0.36
## being_comforted_by_physical_touch              0.01  0.66  0.29  0.01  0.03
## calming_themselves_down                        0.71  0.00  0.18 -0.02  0.08
## controlling_their_emotions                     0.93  0.00  0.06 -0.09 -0.04
## detecting_danger                               0.65  0.08 -0.02  0.13  0.04
## feeling_annoyed                                0.21  0.06  0.09  0.35  0.08
## feeling_bored                                  0.31  0.07  0.11  0.20  0.11
## feeling_calm                                   0.10  0.25  0.33  0.27  0.11
## feeling_confused                               0.13  0.02  0.09  0.44  0.19
## feeling_distressed                             0.00  0.29  0.01  0.65  0.00
## feeling_embarrassed                            0.82  0.05 -0.04  0.00 -0.03
## feeling_excited                                0.05  0.01  0.38  0.11  0.35
## feeling_frustrated                             0.10  0.11  0.17  0.44  0.09
## feeling_guilty                                 0.87  0.10 -0.04 -0.01 -0.08
## feeling_happy                                 -0.06  0.13  0.50  0.13  0.30
## feeling_helpless                               0.30  0.03  0.20  0.44 -0.11
## feeling_hopeless                               0.64 -0.02  0.09  0.22 -0.13
## feeling_lonely                                 0.15  0.04  0.38  0.35 -0.02
## feeling_loved                                  0.02  0.06  0.89 -0.03 -0.04
## feeling_neglected                              0.14  0.16  0.35  0.38 -0.09
## feeling_overwhelmed                            0.17 -0.01  0.14  0.54  0.06
## feeling_pain                                  -0.01  0.86 -0.02  0.05 -0.02
## feeling_physically_uncomfortable               0.01  0.61 -0.08  0.37  0.11
## feeling_pleasure                               0.06  0.18  0.28  0.32  0.22
## feeling_pride                                  0.82 -0.05  0.03  0.07  0.00
## feeling_sad                                    0.02  0.16  0.39  0.20  0.07
## feeling_safe                                   0.05  0.17  0.57  0.21  0.06
## feeling_scared                                -0.07  0.31  0.17  0.33  0.15
## feeling_textures_(for_example,_smooth,_rough)  0.08  0.31  0.15  0.13  0.38
## feeling_thirsty                                0.01  0.85 -0.01 -0.03  0.03
## feeling_tired                                  0.00  0.83  0.05  0.05 -0.05
## feeling_too_hot_or_too_cold                    0.03  0.68  0.02  0.18  0.14
## feeling_worried                                0.39  0.03  0.14  0.29 -0.03
## finding_something_funny                        0.11  0.06  0.29 -0.02  0.37
## focusing_on_a_goal                             0.89 -0.05  0.01  0.07  0.07
## getting_angry                                  0.08  0.08  0.23  0.25  0.09
## getting_hungry                                -0.05  0.94  0.01 -0.09 -0.16
## getting_hurt_feelings                          0.41  0.06  0.21  0.07  0.03
## getting_pleasure_from_music                    0.13  0.12  0.33  0.17  0.29
## having_goals                                   0.94 -0.05  0.00  0.08 -0.02
## having_self_control                            0.96 -0.01  0.01 -0.04  0.00
## having_thoughts                                0.30  0.10  0.27  0.09  0.27
## having_wants_and_desires                       0.27  0.10  0.13  0.33  0.07
## hearing_sounds                                -0.02  0.72 -0.01  0.00  0.25
## imagining_things                               0.53  0.04  0.17  0.00  0.15
## learning_from_other_people                     0.17  0.00  0.31  0.09  0.38
## listening_to_somebody                          0.21  0.14  0.19  0.07  0.35
## loving_somebody                                0.12 -0.06  0.66  0.02  0.11
## making_choices                                 0.70 -0.04  0.06  0.04  0.22
## planning                                       1.00 -0.04 -0.05  0.02  0.00
## reasoning_about_things                         0.94 -0.01  0.01 -0.03  0.02
## recognizing_others_emotions                    0.52 -0.04  0.16  0.08  0.19
## recognizing_somebody_else                      0.12  0.22  0.29 -0.05  0.38
## remembering_things                             0.56  0.04  0.16 -0.05  0.28
## seeing                                         0.06  0.49  0.06 -0.10  0.39
## telling_right_from_wrong                       0.91  0.07 -0.04 -0.05 -0.02
## thinking_before_they_act                       0.96  0.01  0.01 -0.02  0.00
## understanding_what_somebody_else_is_thinking   0.89 -0.04 -0.03  0.02 -0.02
##                                                 MR3   h2   u2 com
## being_afraid_of_somebody                       0.32 0.76 0.24 3.9
## being_angry_at_somebody                        0.40 0.83 0.17 2.6
## being_aware_of_things                          0.01 0.68 0.32 3.6
## being_comforted_by_physical_touch             -0.20 0.66 0.34 1.6
## calming_themselves_down                       -0.02 0.71 0.29 1.2
## controlling_their_emotions                    -0.02 0.79 0.21 1.0
## detecting_danger                               0.11 0.68 0.32 1.2
## feeling_annoyed                                0.37 0.77 0.23 2.9
## feeling_bored                                  0.36 0.78 0.22 3.1
## feeling_calm                                  -0.11 0.60 0.40 3.6
## feeling_confused                               0.24 0.72 0.28 2.3
## feeling_distressed                             0.00 0.70 0.30 1.4
## feeling_embarrassed                            0.20 0.85 0.15 1.1
## feeling_excited                                0.20 0.76 0.24 2.8
## feeling_frustrated                             0.22 0.74 0.26 2.2
## feeling_guilty                                 0.17 0.86 0.14 1.1
## feeling_happy                                  0.01 0.71 0.29 2.0
## feeling_helpless                               0.11 0.67 0.33 2.5
## feeling_hopeless                               0.12 0.72 0.28 1.5
## feeling_lonely                                 0.14 0.71 0.29 2.6
## feeling_loved                                  0.01 0.81 0.19 1.0
## feeling_neglected                              0.06 0.67 0.33 2.8
## feeling_overwhelmed                            0.10 0.67 0.33 1.4
## feeling_pain                                   0.03 0.76 0.24 1.0
## feeling_physically_uncomfortable              -0.06 0.73 0.27 1.8
## feeling_pleasure                              -0.02 0.67 0.33 3.5
## feeling_pride                                  0.08 0.83 0.17 1.0
## feeling_sad                                    0.24 0.70 0.30 2.7
## feeling_safe                                  -0.09 0.69 0.31 1.6
## feeling_scared                                 0.19 0.69 0.31 3.7
## feeling_textures_(for_example,_smooth,_rough)  0.01 0.68 0.32 2.6
## feeling_thirsty                                0.06 0.74 0.26 1.0
## feeling_tired                                 -0.02 0.73 0.27 1.0
## feeling_too_hot_or_too_cold                   -0.07 0.72 0.28 1.2
## feeling_worried                                0.26 0.75 0.25 3.0
## finding_something_funny                        0.33 0.78 0.22 3.2
## focusing_on_a_goal                            -0.11 0.82 0.18 1.1
## getting_angry                                  0.40 0.75 0.25 2.7
## getting_hungry                                 0.08 0.76 0.24 1.1
## getting_hurt_feelings                          0.32 0.75 0.25 2.6
## getting_pleasure_from_music                    0.02 0.68 0.32 3.2
## having_goals                                  -0.10 0.84 0.16 1.0
## having_self_control                           -0.04 0.86 0.14 1.0
## having_thoughts                                0.09 0.72 0.28 3.6
## having_wants_and_desires                       0.12 0.60 0.40 2.9
## hearing_sounds                                 0.00 0.70 0.30 1.2
## imagining_things                               0.19 0.75 0.25 1.7
## learning_from_other_people                     0.17 0.77 0.23 2.9
## listening_to_somebody                          0.12 0.64 0.36 3.1
## loving_somebody                                0.16 0.77 0.23 1.2
## making_choices                                 0.07 0.83 0.17 1.2
## planning                                      -0.11 0.87 0.13 1.0
## reasoning_about_things                        -0.03 0.84 0.16 1.0
## recognizing_others_emotions                    0.09 0.68 0.32 1.6
## recognizing_somebody_else                      0.18 0.74 0.26 3.4
## remembering_things                             0.10 0.77 0.23 1.7
## seeing                                         0.04 0.59 0.41 2.1
## telling_right_from_wrong                       0.11 0.86 0.14 1.1
## thinking_before_they_act                      -0.06 0.85 0.15 1.0
## understanding_what_somebody_else_is_thinking   0.02 0.78 0.22 1.0
## 
##                         MR1  MR2  MR5  MR4  MR6  MR3
## SS loadings           16.56 7.47 7.04 5.69 4.08 3.67
## Proportion Var         0.28 0.12 0.12 0.09 0.07 0.06
## Cumulative Var         0.28 0.40 0.52 0.61 0.68 0.74
## Proportion Explained   0.37 0.17 0.16 0.13 0.09 0.08
## Cumulative Proportion  0.37 0.54 0.70 0.83 0.92 1.00
## 
##  With factor correlations of 
##      MR1  MR2  MR5  MR4  MR6  MR3
## MR1 1.00 0.14 0.56 0.52 0.41 0.53
## MR2 0.14 1.00 0.51 0.51 0.42 0.26
## MR5 0.56 0.51 1.00 0.55 0.58 0.49
## MR4 0.52 0.51 0.55 1.00 0.36 0.41
## MR6 0.41 0.42 0.58 0.36 1.00 0.32
## MR3 0.53 0.26 0.49 0.41 0.32 1.00
## 
## Mean item complexity =  2
## Test of the hypothesis that 6 factors are sufficient.
## 
## The degrees of freedom for the null model are  1770  and the objective function was  73.6 with Chi Square of  64855.87
## The degrees of freedom for the model are 1425  and the objective function was  4.2 
## 
## The root mean square of the residuals (RMSR) is  0.01 
## The df corrected root mean square of the residuals is  0.01 
## 
## The harmonic number of observations is  903 with the empirical chi square  534.58  with prob <  1 
## The total number of observations was  903  with Likelihood Chi Square =  3684.27  with prob <  2e-199 
## 
## Tucker Lewis Index of factoring reliability =  0.955
## RMSEA index =  0.042  and the 90 % confidence intervals are  0.04 0.044
## BIC =  -6013.88
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy             
##                                                    MR1  MR2  MR5  MR4  MR6  MR3
## Correlation of (regression) scores with factors   0.99 0.98 0.96 0.94 0.92 0.92
## Multiple R square of scores with factors          0.99 0.95 0.93 0.89 0.85 0.85
## Minimum correlation of possible factor scores     0.97 0.91 0.85 0.78 0.71 0.70
## Joining, by = "capacity"
## Joining, by = "factor"
## Joining, by = "factor"

## Saving 4.5 x 5.4 in image
## Saving 4.5 x 5.4 in image

Weisman et al.’s (2017) factor retention criteria

## [1] 2
## Factor Analysis using method =  minres
## Call: fa(r = d1_all, nfactors = s1_weismanetal, rotate = "oblimin")
## Standardized loadings (pattern matrix) based upon correlation matrix
##                                                 MR1   MR2   h2   u2 com
## being_afraid_of_somebody                       0.38  0.60 0.71 0.29 1.7
## being_angry_at_somebody                        0.69  0.32 0.77 0.23 1.4
## being_aware_of_things                          0.40  0.54 0.63 0.37 1.8
## being_comforted_by_physical_touch             -0.16  0.81 0.58 0.42 1.1
## calming_themselves_down                        0.80  0.07 0.69 0.31 1.0
## controlling_their_emotions                     0.92 -0.13 0.76 0.24 1.0
## detecting_danger                               0.75  0.13 0.66 0.34 1.1
## feeling_annoyed                                0.56  0.43 0.70 0.30 1.9
## feeling_bored                                  0.62  0.37 0.73 0.27 1.6
## feeling_calm                                   0.22  0.63 0.57 0.43 1.2
## feeling_confused                               0.48  0.48 0.67 0.33 2.0
## feeling_distressed                             0.14  0.66 0.54 0.46 1.1
## feeling_embarrassed                            0.91 -0.01 0.82 0.18 1.0
## feeling_excited                                0.42  0.54 0.67 0.33 1.9
## feeling_frustrated                             0.41  0.56 0.68 0.32 1.8
## feeling_guilty                                 0.91 -0.01 0.81 0.19 1.0
## feeling_happy                                  0.22  0.68 0.63 0.37 1.2
## feeling_helpless                               0.56  0.34 0.59 0.41 1.6
## feeling_hopeless                               0.80  0.05 0.68 0.32 1.0
## feeling_lonely                                 0.48  0.48 0.65 0.35 2.0
## feeling_loved                                  0.33  0.56 0.58 0.42 1.6
## feeling_neglected                              0.37  0.54 0.60 0.40 1.8
## feeling_overwhelmed                            0.48  0.42 0.58 0.42 2.0
## feeling_pain                                  -0.24  0.88 0.65 0.35 1.1
## feeling_physically_uncomfortable              -0.07  0.82 0.63 0.37 1.0
## feeling_pleasure                               0.28  0.64 0.64 0.36 1.4
## feeling_pride                                  0.93 -0.05 0.82 0.18 1.0
## feeling_sad                                    0.34  0.61 0.67 0.33 1.6
## feeling_safe                                   0.26  0.63 0.62 0.38 1.3
## feeling_scared                                 0.15  0.74 0.68 0.32 1.1
## feeling_textures_(for_example,_smooth,_rough)  0.20  0.69 0.63 0.37 1.2
## feeling_thirsty                               -0.20  0.86 0.63 0.37 1.1
## feeling_tired                                 -0.22  0.87 0.63 0.37 1.1
## feeling_too_hot_or_too_cold                   -0.10  0.85 0.66 0.34 1.0
## feeling_worried                                0.67  0.29 0.71 0.29 1.4
## finding_something_funny                        0.46  0.50 0.66 0.34 2.0
## focusing_on_a_goal                             0.92 -0.08 0.78 0.22 1.0
## getting_angry                                  0.47  0.50 0.68 0.32 2.0
## getting_hungry                                -0.33  0.84 0.57 0.43 1.3
## getting_hurt_feelings                          0.68  0.29 0.72 0.28 1.3
## getting_pleasure_from_music                    0.37  0.57 0.64 0.36 1.7
## having_goals                                   0.94 -0.12 0.80 0.20 1.0
## having_self_control                            0.96 -0.13 0.82 0.18 1.0
## having_thoughts                                0.52  0.45 0.69 0.31 2.0
## having_wants_and_desires                       0.48  0.41 0.58 0.42 1.9
## hearing_sounds                                -0.17  0.85 0.63 0.37 1.1
## imagining_things                               0.74  0.22 0.73 0.27 1.2
## learning_from_other_people                     0.51  0.47 0.69 0.31 2.0
## listening_to_somebody                          0.42  0.50 0.60 0.40 1.9
## loving_somebody                                0.50  0.44 0.64 0.36 2.0
## making_choices                                 0.86  0.09 0.81 0.19 1.0
## planning                                       0.97 -0.18 0.82 0.18 1.1
## reasoning_about_things                         0.94 -0.11 0.81 0.19 1.0
## recognizing_others_emotions                    0.72  0.18 0.67 0.33 1.1
## recognizing_somebody_else                      0.33  0.60 0.66 0.34 1.6
## remembering_things                             0.72  0.23 0.73 0.27 1.2
## seeing                                         0.03  0.69 0.49 0.51 1.0
## telling_right_from_wrong                       0.93 -0.04 0.83 0.17 1.0
## thinking_before_they_act                       0.94 -0.10 0.81 0.19 1.0
## understanding_what_somebody_else_is_thinking   0.93 -0.14 0.76 0.24 1.0
## 
##                         MR1   MR2
## SS loadings           23.33 17.58
## Proportion Var         0.39  0.29
## Cumulative Var         0.39  0.68
## Proportion Explained   0.57  0.43
## Cumulative Proportion  0.57  1.00
## 
##  With factor correlations of 
##      MR1  MR2
## MR1 1.00 0.44
## MR2 0.44 1.00
## 
## Mean item complexity =  1.4
## Test of the hypothesis that 2 factors are sufficient.
## 
## The degrees of freedom for the null model are  1770  and the objective function was  73.6 with Chi Square of  64855.87
## The degrees of freedom for the model are 1651  and the objective function was  10.52 
## 
## The root mean square of the residuals (RMSR) is  0.03 
## The df corrected root mean square of the residuals is  0.03 
## 
## The harmonic number of observations is  903 with the empirical chi square  3597.69  with prob <  4e-146 
## The total number of observations was  903  with Likelihood Chi Square =  9258.55  with prob <  0 
## 
## Tucker Lewis Index of factoring reliability =  0.871
## RMSEA index =  0.071  and the 90 % confidence intervals are  0.07 0.073
## BIC =  -1977.7
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy             
##                                                    MR1  MR2
## Correlation of (regression) scores with factors   0.99 0.99
## Multiple R square of scores with factors          0.99 0.98
## Minimum correlation of possible factor scores     0.98 0.95
## Joining, by = "capacity"
## Joining, by = "factor"
## Joining, by = "factor"

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## Saving 4.5 x 5.4 in image

Study 2

Exploratory factor analyses (EFAs)

Parallel analysis

## Parallel analysis suggests that the number of factors =  4  and the number of components =  4
## Factor Analysis using method =  minres
## Call: fa(r = d2_all, nfactors = s2_parallel$nfact, rotate = "oblimin")
## Standardized loadings (pattern matrix) based upon correlation matrix
##                                    MR2   MR1   MR4   MR3   h2   u2 com
## having_self_control               0.96 -0.02 -0.01  0.01 0.89 0.11 1.0
## controlling_their_emotions        0.94 -0.04  0.01 -0.01 0.85 0.15 1.0
## telling_right_from_wrong          0.93 -0.03  0.04  0.00 0.88 0.12 1.0
## planning                          0.90  0.07 -0.05  0.00 0.82 0.18 1.0
## reasoning_about_things            0.89  0.05  0.02  0.00 0.86 0.14 1.0
## feeling_overwhelmed               0.02  0.84  0.10 -0.06 0.77 0.23 1.0
## feeling_distressed               -0.01  0.81 -0.09  0.19 0.75 0.25 1.1
## feeling_frustrated                0.03  0.80  0.08  0.03 0.78 0.22 1.0
## feeling_helpless                  0.08  0.77  0.09 -0.05 0.70 0.30 1.1
## feeling_lonely                    0.05  0.60  0.27  0.03 0.70 0.30 1.4
## feeling_happy                    -0.07  0.05  0.85  0.09 0.78 0.22 1.0
## finding_something_funny           0.09 -0.01  0.83  0.02 0.78 0.22 1.0
## feeling_excited                  -0.01  0.16  0.79 -0.01 0.78 0.22 1.1
## loving_somebody                   0.15  0.07  0.66  0.01 0.63 0.37 1.1
## learning_from_other_people        0.31  0.03  0.48  0.05 0.55 0.45 1.7
## getting_hungry                   -0.01 -0.06  0.02  0.88 0.73 0.27 1.0
## feeling_pain                      0.03  0.04 -0.01  0.86 0.78 0.22 1.0
## feeling_tired                    -0.01  0.16  0.02  0.72 0.69 0.31 1.1
## hearing_sounds                    0.01 -0.12  0.29  0.67 0.57 0.43 1.4
## feeling_physically_uncomfortable  0.02  0.41 -0.12  0.56 0.64 0.36 2.0
## 
##                        MR2  MR1  MR4  MR3
## SS loadings           4.64 3.74 3.42 3.15
## Proportion Var        0.23 0.19 0.17 0.16
## Cumulative Var        0.23 0.42 0.59 0.75
## Proportion Explained  0.31 0.25 0.23 0.21
## Cumulative Proportion 0.31 0.56 0.79 1.00
## 
##  With factor correlations of 
##      MR2  MR1  MR4  MR3
## MR2 1.00 0.43 0.54 0.09
## MR1 0.43 1.00 0.60 0.54
## MR4 0.54 0.60 1.00 0.40
## MR3 0.09 0.54 0.40 1.00
## 
## Mean item complexity =  1.2
## Test of the hypothesis that 4 factors are sufficient.
## 
## The degrees of freedom for the null model are  190  and the objective function was  19.29 with Chi Square of  76082.56
## The degrees of freedom for the model are 116  and the objective function was  0.34 
## 
## The root mean square of the residuals (RMSR) is  0.01 
## The df corrected root mean square of the residuals is  0.01 
## 
## The harmonic number of observations is  3952 with the empirical chi square  187.9  with prob <  2.7e-05 
## The total number of observations was  3952  with Likelihood Chi Square =  1332.54  with prob <  1e-205 
## 
## Tucker Lewis Index of factoring reliability =  0.974
## RMSEA index =  0.052  and the 90 % confidence intervals are  0.049 0.054
## BIC =  371.83
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy             
##                                                    MR2  MR1  MR4  MR3
## Correlation of (regression) scores with factors   0.98 0.97 0.96 0.96
## Multiple R square of scores with factors          0.97 0.93 0.92 0.91
## Minimum correlation of possible factor scores     0.94 0.86 0.85 0.83
## Warning in if (is.na(factor_names)) {: the condition has length > 1 and only the
## first element will be used
## Joining, by = "capacity"
## Joining, by = "factor"
## Joining, by = "factor"

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## Saving 4.5 x 2.25 in image

Minimizing BIC

## Warning in GPFoblq(L, Tmat = Tmat, normalize = normalize, eps = eps, maxit =
## maxit, : convergence not obtained in GPFoblq. 1000 iterations used.
## Factor Analysis using method =  minres
## Call: fa(r = d2_all, nfactors = s2_minbic$nfact, rotate = "oblimin")
## Standardized loadings (pattern matrix) based upon correlation matrix
##                                    MR2   MR3   MR4   MR1   MR5   MR6   MR7
## controlling_their_emotions        0.96  0.01  0.03 -0.03  0.00 -0.06 -0.04
## feeling_distressed                0.02  0.05 -0.01  0.84  0.02  0.02  0.04
## feeling_excited                   0.04  0.00  0.90  0.04  0.02 -0.05  0.02
## feeling_frustrated                0.06  0.05  0.17  0.66  0.07 -0.01  0.01
## feeling_happy                    -0.03  0.05  0.76  0.06  0.06  0.07 -0.05
## feeling_helpless                  0.06  0.04  0.01  0.17  0.63 -0.01  0.04
## feeling_lonely                    0.01  0.02  0.04 -0.02  0.88  0.02  0.00
## feeling_overwhelmed               0.02  0.00  0.09  0.57  0.21  0.08  0.01
## feeling_pain                      0.02  0.76  0.02 -0.02  0.10 -0.04  0.12
## feeling_physically_uncomfortable -0.01  0.38  0.01  0.30  0.08  0.00  0.30
## feeling_tired                     0.01  0.71  0.02  0.19  0.02 -0.02 -0.03
## finding_something_funny           0.08  0.03  0.63 -0.05  0.06  0.23  0.03
## getting_hungry                   -0.01  0.94 -0.05 -0.02 -0.01  0.02 -0.05
## having_self_control               0.98  0.02  0.01  0.00 -0.01 -0.04 -0.04
## hearing_sounds                    0.00  0.63  0.24 -0.06 -0.04  0.08  0.06
## learning_from_other_people        0.19  0.04  0.11  0.08  0.03  0.52  0.06
## loving_somebody                   0.10  0.05  0.21  0.07  0.22  0.40 -0.18
## planning                          0.88 -0.03 -0.04  0.04  0.03  0.03  0.05
## reasoning_about_things            0.86 -0.02 -0.01  0.00  0.04  0.08  0.08
## telling_right_from_wrong          0.92  0.00  0.01  0.00 -0.02  0.04 -0.01
##                                    MR8   h2   u2 com
## controlling_their_emotions       -0.01 0.86 0.14 1.0
## feeling_distressed               -0.11 0.82 0.18 1.0
## feeling_excited                   0.06 0.86 0.14 1.0
## feeling_frustrated                0.12 0.80 0.20 1.3
## feeling_happy                    -0.12 0.80 0.20 1.1
## feeling_helpless                  0.18 0.75 0.25 1.4
## feeling_lonely                   -0.07 0.83 0.17 1.0
## feeling_overwhelmed               0.19 0.78 0.22 1.6
## feeling_pain                     -0.08 0.78 0.22 1.1
## feeling_physically_uncomfortable -0.08 0.70 0.30 3.1
## feeling_tired                    -0.02 0.70 0.30 1.2
## finding_something_funny           0.02 0.77 0.23 1.4
## getting_hungry                    0.04 0.77 0.23 1.0
## having_self_control              -0.01 0.90 0.10 1.0
## hearing_sounds                   -0.02 0.57 0.43 1.4
## learning_from_other_people        0.03 0.64 0.36 1.5
## loving_somebody                  -0.08 0.70 0.30 3.1
## planning                          0.00 0.82 0.18 1.0
## reasoning_about_things            0.02 0.86 0.14 1.0
## telling_right_from_wrong          0.00 0.88 0.12 1.0
## 
##                        MR2  MR3  MR4  MR1  MR5  MR6  MR7  MR8
## SS loadings           4.55 2.91 2.55 2.29 1.90 0.94 0.28 0.18
## Proportion Var        0.23 0.15 0.13 0.11 0.09 0.05 0.01 0.01
## Cumulative Var        0.23 0.37 0.50 0.61 0.71 0.76 0.77 0.78
## Proportion Explained  0.29 0.19 0.16 0.15 0.12 0.06 0.02 0.01
## Cumulative Proportion 0.29 0.48 0.64 0.79 0.91 0.97 0.99 1.00
## 
##  With factor correlations of 
##      MR2   MR3  MR4  MR1  MR5   MR6   MR7   MR8
## MR2 1.00  0.09 0.49 0.34 0.49  0.54  0.08  0.15
## MR3 0.09  1.00 0.42 0.54 0.47  0.21  0.37 -0.25
## MR4 0.49  0.42 1.00 0.51 0.68  0.66  0.01  0.04
## MR1 0.34  0.54 0.51 1.00 0.80  0.23  0.36  0.11
## MR5 0.49  0.47 0.68 0.80 1.00  0.46  0.22  0.08
## MR6 0.54  0.21 0.66 0.23 0.46  1.00  0.00 -0.05
## MR7 0.08  0.37 0.01 0.36 0.22  0.00  1.00 -0.04
## MR8 0.15 -0.25 0.04 0.11 0.08 -0.05 -0.04  1.00
## 
## Mean item complexity =  1.4
## Test of the hypothesis that 8 factors are sufficient.
## 
## The degrees of freedom for the null model are  190  and the objective function was  19.29 with Chi Square of  76082.56
## The degrees of freedom for the model are 58  and the objective function was  0.08 
## 
## The root mean square of the residuals (RMSR) is  0 
## The df corrected root mean square of the residuals is  0.01 
## 
## The harmonic number of observations is  3952 with the empirical chi square  25.8  with prob <  1 
## The total number of observations was  3952  with Likelihood Chi Square =  326.4  with prob <  4.7e-39 
## 
## Tucker Lewis Index of factoring reliability =  0.988
## RMSEA index =  0.034  and the 90 % confidence intervals are  0.031 0.038
## BIC =  -153.95
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy             
##                                                    MR2  MR3  MR4  MR1  MR5  MR6
## Correlation of (regression) scores with factors   0.99 0.96 0.96 0.96 0.95 0.86
## Multiple R square of scores with factors          0.97 0.91 0.93 0.91 0.91 0.73
## Minimum correlation of possible factor scores     0.94 0.82 0.85 0.82 0.81 0.47
##                                                     MR7   MR8
## Correlation of (regression) scores with factors    0.69  0.67
## Multiple R square of scores with factors           0.48  0.46
## Minimum correlation of possible factor scores     -0.04 -0.09
## Joining, by = "capacity"
## Joining, by = "factor"
## Joining, by = "factor"

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## Saving 5.5 x 1.92 in image

Weisman et al.’s (2017) factor retention criteria

## [1] 4
## Factor Analysis using method =  minres
## Call: fa(r = d2_all, nfactors = s2_weismanetal, rotate = "oblimin")
## Standardized loadings (pattern matrix) based upon correlation matrix
##                                    MR2   MR1   MR4   MR3   h2   u2 com
## controlling_their_emotions        0.94 -0.04  0.01 -0.01 0.85 0.15 1.0
## feeling_distressed               -0.01  0.81 -0.09  0.19 0.75 0.25 1.1
## feeling_excited                  -0.01  0.16  0.79 -0.01 0.78 0.22 1.1
## feeling_frustrated                0.03  0.80  0.08  0.03 0.78 0.22 1.0
## feeling_happy                    -0.07  0.05  0.85  0.09 0.78 0.22 1.0
## feeling_helpless                  0.08  0.77  0.09 -0.05 0.70 0.30 1.1
## feeling_lonely                    0.05  0.60  0.27  0.03 0.70 0.30 1.4
## feeling_overwhelmed               0.02  0.84  0.10 -0.06 0.77 0.23 1.0
## feeling_pain                      0.03  0.04 -0.01  0.86 0.78 0.22 1.0
## feeling_physically_uncomfortable  0.02  0.41 -0.12  0.56 0.64 0.36 2.0
## feeling_tired                    -0.01  0.16  0.02  0.72 0.69 0.31 1.1
## finding_something_funny           0.09 -0.01  0.83  0.02 0.78 0.22 1.0
## getting_hungry                   -0.01 -0.06  0.02  0.88 0.73 0.27 1.0
## having_self_control               0.96 -0.02 -0.01  0.01 0.89 0.11 1.0
## hearing_sounds                    0.01 -0.12  0.29  0.67 0.57 0.43 1.4
## learning_from_other_people        0.31  0.03  0.48  0.05 0.55 0.45 1.7
## loving_somebody                   0.15  0.07  0.66  0.01 0.63 0.37 1.1
## planning                          0.90  0.07 -0.05  0.00 0.82 0.18 1.0
## reasoning_about_things            0.89  0.05  0.02  0.00 0.86 0.14 1.0
## telling_right_from_wrong          0.93 -0.03  0.04  0.00 0.88 0.12 1.0
## 
##                        MR2  MR1  MR4  MR3
## SS loadings           4.64 3.74 3.42 3.15
## Proportion Var        0.23 0.19 0.17 0.16
## Cumulative Var        0.23 0.42 0.59 0.75
## Proportion Explained  0.31 0.25 0.23 0.21
## Cumulative Proportion 0.31 0.56 0.79 1.00
## 
##  With factor correlations of 
##      MR2  MR1  MR4  MR3
## MR2 1.00 0.43 0.54 0.09
## MR1 0.43 1.00 0.60 0.54
## MR4 0.54 0.60 1.00 0.40
## MR3 0.09 0.54 0.40 1.00
## 
## Mean item complexity =  1.2
## Test of the hypothesis that 4 factors are sufficient.
## 
## The degrees of freedom for the null model are  190  and the objective function was  19.29 with Chi Square of  76082.56
## The degrees of freedom for the model are 116  and the objective function was  0.34 
## 
## The root mean square of the residuals (RMSR) is  0.01 
## The df corrected root mean square of the residuals is  0.01 
## 
## The harmonic number of observations is  3952 with the empirical chi square  187.9  with prob <  2.7e-05 
## The total number of observations was  3952  with Likelihood Chi Square =  1332.54  with prob <  1e-205 
## 
## Tucker Lewis Index of factoring reliability =  0.974
## RMSEA index =  0.052  and the 90 % confidence intervals are  0.049 0.054
## BIC =  371.83
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy             
##                                                    MR2  MR1  MR4  MR3
## Correlation of (regression) scores with factors   0.98 0.97 0.96 0.96
## Multiple R square of scores with factors          0.97 0.93 0.92 0.91
## Minimum correlation of possible factor scores     0.94 0.86 0.85 0.83
## Joining, by = "capacity"
## Joining, by = "factor"
## Joining, by = "factor"

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## Saving 4.5 x 2.25 in image

Developmental trajectories

## Joining, by = "capacity"
## `summarise()` has grouped output by 'factor'. You can override using the `.groups` argument.
## 
## Family: Beta regression 
## Link function: logit 
## 
## Formula:
## response ~ s(target_year, by = factor) + factor
## 
## Parametric coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   -1.26325    0.07696  -16.41   <2e-16 ***
## factorbod_cog  4.82455    0.05306   90.92   <2e-16 ***
## factorneg_cog  3.05376    0.05003   61.04   <2e-16 ***
## factorsoc_cog  3.13147    0.04991   62.74   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Approximate significance of smooth terms:
##                                              edf Ref.df      F p-value    
## s(target_year):factorBodily sensations     6.072  6.072  364.8  <2e-16 ***
## s(target_year):factorNegative affect       7.700  7.700 1535.9  <2e-16 ***
## s(target_year):factorSocial connection     8.626  8.626 2351.3  <2e-16 ***
## s(target_year):factorCognition and control 8.134  8.134 3396.9  <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## R-sq.(adj) =  0.504   
##   Scale est. = 0.30004   n = 79040
## `summarise()` has grouped output by 'ResponseId', 'factor'. You can override using the `.groups` argument.

Study 3

Developmental trajectories

## `summarise()` has grouped output by 'factor'. You can override using the `.groups` argument.
## 
## Family: Beta regression 
## Link function: logit 
## 
## Formula:
## response ~ s(target_year, by = factor) + factor
## 
## Parametric coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   -1.45908    0.09301  -15.69   <2e-16 ***
## factorbod_cog  6.00076    0.11381   52.73   <2e-16 ***
## factorneg_cog  3.48665    0.10836   32.18   <2e-16 ***
## factorsoc_cog  3.14862    0.10752   29.28   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Approximate significance of smooth terms:
##                                              edf Ref.df      F p-value    
## s(target_year):factorBodily sensations     8.127  8.127  176.0  <2e-16 ***
## s(target_year):factorNegative affect       8.345  8.345  748.5  <2e-16 ***
## s(target_year):factorSocial connection     8.853  8.853 1744.7  <2e-16 ***
## s(target_year):factorCognition and control 8.445  8.445 1782.2  <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## R-sq.(adj) =   0.52   
##   Scale est. = 0.19709   n = 31304
## `summarise()` has grouped output by 'ResponseId', 'factor'. You can override using the `.groups` argument.
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
Perceived developmental trajectories for four domains of mental life (Studies 2-3). Lighter lines represent individual participants’ responses, black points correspond to mean responses across the sample, error bars are bootstrapped 95% confidence intervals, and thick red lines are predictions from our generalized additive models (beta regressions). In Study 2 (Panel A), participants assessed 5 capacities within each domain, and assessed all capacities for a given target age before moving on to the next target age. In Study 3 (Panel B), participants assessed 2 capacities within each domain, and assessed a single capacity for all target ages before moving on to the next capacity.

Perceived developmental trajectories for four domains of mental life (Studies 2-3). Lighter lines represent individual participants’ responses, black points correspond to mean responses across the sample, error bars are bootstrapped 95% confidence intervals, and thick red lines are predictions from our generalized additive models (beta regressions). In Study 2 (Panel A), participants assessed 5 capacities within each domain, and assessed all capacities for a given target age before moving on to the next target age. In Study 3 (Panel B), participants assessed 2 capacities within each domain, and assessed a single capacity for all target ages before moving on to the next capacity.

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## Saving 4 x 4.8 in image
Comparing variability in ratings across domains
## `summarise()` has grouped output by 'factor', 'capacity'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'factor', 'capacity'. You can override using the `.groups` argument.
## Warning: Removed 4 row(s) containing missing values (geom_path).
## Warning: Removed 4 rows containing missing values (geom_point).
## Warning: Removed 1 rows containing missing values (geom_segment).
Variance of capacity attributions in four domains of mental life (Studies 2-3). Lighter dots and lines represent variance across participnts for a particular capacity at a particular target age, red points correpond to mean variance across capacities at birth, black points correspond to mean variance across capacities and across all target ages, and error bars are bootstrapped 95% confidence intervals. In Study 2 (Panel A), participants assessed 5 capacities within each domain, and assessed all capacities for a given target age before moving on to the next target age. In Study 3 (Panel B), participants assessed 2 capacities within each domain, and assessed a single capacity for all target ages before moving on to the next capacity.

Variance of capacity attributions in four domains of mental life (Studies 2-3). Lighter dots and lines represent variance across participnts for a particular capacity at a particular target age, red points correpond to mean variance across capacities at birth, black points correspond to mean variance across capacities and across all target ages, and error bars are bootstrapped 95% confidence intervals. In Study 2 (Panel A), participants assessed 5 capacities within each domain, and assessed all capacities for a given target age before moving on to the next target age. In Study 3 (Panel B), participants assessed 2 capacities within each domain, and assessed a single capacity for all target ages before moving on to the next capacity.

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Developmental mechanisms: Ratings

Dimensionality reduction

Parallel analysis
## Parallel analysis suggests that the number of factors =  4  and the number of components =  2
## Factor Analysis using method =  minres
## Call: fa(r = d3_mech_ratings_wide, nfactors = s3_parallel$nfact, rotate = "varimax")
## Standardized loadings (pattern matrix) based upon correlation matrix
##                    MR1   MR3  MR4   MR2   h2    u2 com
## observes_people   0.87  0.33 0.25 -0.06 0.93 0.069 1.5
## interacts_people  0.82  0.37 0.24 -0.09 0.87 0.126 1.6
## observes_objects  0.66  0.26 0.46  0.05 0.72 0.277 2.2
## people_teach      0.35  0.82 0.20 -0.02 0.85 0.154 1.5
## experiments       0.44  0.64 0.33  0.02 0.71 0.287 2.3
## senses_improve    0.32  0.15 0.69  0.22 0.65 0.350 1.8
## body_grows        0.11  0.14 0.55  0.44 0.53 0.474 2.2
## brain_changes     0.42  0.26 0.49 -0.05 0.48 0.518 2.5
## womb_experiences  0.03  0.05 0.14  0.81 0.67 0.328 1.1
## preprogrammed    -0.26 -0.29 0.04  0.43 0.33 0.666 2.5
## 
##                        MR1  MR3  MR4  MR2
## SS loadings           2.54 1.60 1.52 1.09
## Proportion Var        0.25 0.16 0.15 0.11
## Cumulative Var        0.25 0.41 0.57 0.68
## Proportion Explained  0.38 0.24 0.22 0.16
## Cumulative Proportion 0.38 0.61 0.84 1.00
## 
## Mean item complexity =  1.9
## Test of the hypothesis that 4 factors are sufficient.
## 
## The degrees of freedom for the null model are  45  and the objective function was  6.2 with Chi Square of  14888.56
## The degrees of freedom for the model are 11  and the objective function was  0.04 
## 
## The root mean square of the residuals (RMSR) is  0.01 
## The df corrected root mean square of the residuals is  0.02 
## 
## The harmonic number of observations is  2408 with the empirical chi square  21.3  with prob <  0.03 
## The total number of observations was  2408  with Likelihood Chi Square =  103.94  with prob <  3e-17 
## 
## Tucker Lewis Index of factoring reliability =  0.974
## RMSEA index =  0.059  and the 90 % confidence intervals are  0.049 0.07
## BIC =  18.28
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy             
##                                                    MR1  MR3  MR4  MR2
## Correlation of (regression) scores with factors   0.93 0.89 0.79 0.83
## Multiple R square of scores with factors          0.87 0.78 0.62 0.70
## Minimum correlation of possible factor scores     0.73 0.57 0.25 0.39
## Warning in if (is.na(factor_names)) {: the condition has length > 1 and only the
## first element will be used
## Joining, by = "capacity"
## Joining, by = "factor"
## Joining, by = "factor"

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Minimizing BIC
## Factor Analysis using method =  minres
## Call: fa(r = d3_mech_ratings_wide, nfactors = s3_minbic$nfact, rotate = "varimax")
## Standardized loadings (pattern matrix) based upon correlation matrix
##                    MR1   MR3   MR2  MR5   MR4   h2    u2 com
## preprogrammed    -0.25 -0.28  0.43 0.05 -0.10 0.34 0.664 2.6
## womb_experiences  0.03  0.04  0.80 0.07  0.00 0.65 0.353 1.0
## body_grows        0.12  0.15  0.51 0.40  0.24 0.51 0.488 2.7
## brain_changes     0.36  0.23  0.01 0.27  0.69 0.73 0.266 2.1
## senses_improve    0.33  0.17  0.28 0.63  0.24 0.67 0.330 2.5
## observes_objects  0.68  0.27  0.08 0.45  0.15 0.77 0.235 2.2
## experiments       0.44  0.64  0.05 0.25  0.19 0.71 0.293 2.3
## observes_people   0.86  0.34 -0.03 0.17  0.22 0.93 0.075 1.5
## interacts_people  0.81  0.37 -0.07 0.15  0.23 0.87 0.128 1.7
## people_teach      0.35  0.84  0.00 0.13  0.14 0.86 0.137 1.5
## 
##                        MR1  MR3  MR2  MR5  MR4
## SS loadings           2.48 1.63 1.18 0.96 0.79
## Proportion Var        0.25 0.16 0.12 0.10 0.08
## Cumulative Var        0.25 0.41 0.53 0.62 0.70
## Proportion Explained  0.35 0.23 0.17 0.14 0.11
## Cumulative Proportion 0.35 0.58 0.75 0.89 1.00
## 
## Mean item complexity =  2
## Test of the hypothesis that 5 factors are sufficient.
## 
## The degrees of freedom for the null model are  45  and the objective function was  6.2 with Chi Square of  14888.56
## The degrees of freedom for the model are 5  and the objective function was  0.01 
## 
## The root mean square of the residuals (RMSR) is  0 
## The df corrected root mean square of the residuals is  0.01 
## 
## The harmonic number of observations is  2408 with the empirical chi square  2.21  with prob <  0.82 
## The total number of observations was  2408  with Likelihood Chi Square =  30.85  with prob <  1e-05 
## 
## Tucker Lewis Index of factoring reliability =  0.984
## RMSEA index =  0.046  and the 90 % confidence intervals are  0.031 0.063
## BIC =  -8.08
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy             
##                                                    MR1  MR3  MR2  MR5  MR4
## Correlation of (regression) scores with factors   0.93 0.90 0.84 0.74 0.75
## Multiple R square of scores with factors          0.86 0.80 0.71 0.54 0.56
## Minimum correlation of possible factor scores     0.72 0.61 0.41 0.09 0.12
## Joining, by = "capacity"
## Joining, by = "factor"
## Joining, by = "factor"

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Weisman et al.’s (2017) factor retention criteria
## [1] 2
## Factor Analysis using method =  minres
## Call: fa(r = d3_mech_ratings_wide, nfactors = s3_weismanetal, rotate = "varimax")
## Standardized loadings (pattern matrix) based upon correlation matrix
##                    MR1   MR2   h2   u2 com
## preprogrammed    -0.40  0.44 0.36 0.64 2.0
## womb_experiences  0.00  0.64 0.40 0.60 1.0
## body_grows        0.30  0.68 0.55 0.45 1.4
## brain_changes     0.64  0.18 0.44 0.56 1.2
## senses_improve    0.55  0.51 0.55 0.45 2.0
## observes_objects  0.80  0.23 0.69 0.31 1.2
## experiments       0.79  0.11 0.63 0.37 1.0
## observes_people   0.91  0.01 0.83 0.17 1.0
## interacts_people  0.91 -0.03 0.82 0.18 1.0
## people_teach      0.74  0.02 0.55 0.45 1.0
## 
##                        MR1  MR2
## SS loadings           4.43 1.41
## Proportion Var        0.44 0.14
## Cumulative Var        0.44 0.58
## Proportion Explained  0.76 0.24
## Cumulative Proportion 0.76 1.00
## 
## Mean item complexity =  1.3
## Test of the hypothesis that 2 factors are sufficient.
## 
## The degrees of freedom for the null model are  45  and the objective function was  6.2 with Chi Square of  14888.56
## The degrees of freedom for the model are 26  and the objective function was  0.58 
## 
## The root mean square of the residuals (RMSR) is  0.04 
## The df corrected root mean square of the residuals is  0.05 
## 
## The harmonic number of observations is  2408 with the empirical chi square  374.7  with prob <  1.8e-63 
## The total number of observations was  2408  with Likelihood Chi Square =  1392.85  with prob <  9.7e-278 
## 
## Tucker Lewis Index of factoring reliability =  0.841
## RMSEA index =  0.148  and the 90 % confidence intervals are  0.141 0.154
## BIC =  1190.4
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy             
##                                                    MR1  MR2
## Correlation of (regression) scores with factors   0.97 0.85
## Multiple R square of scores with factors          0.94 0.73
## Minimum correlation of possible factor scores     0.87 0.45
## Warning in if (is.na(factor_names)) {: the condition has length > 1 and only the
## first element will be used
## Joining, by = "capacity"
## Joining, by = "factor"
## Joining, by = "factor"

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Hierarchical clustering
## The "ward" method has been renamed to "ward.D"; note new "ward.D2"

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Model

## `summarise()` has grouped output by 'ResponseId'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'ResponseId', 'dev_factor_cluster', 'dev_factor'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'ResponseId', 'dev_factor_cluster'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'dev_factor_cluster'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'ResponseId', 'dev_factor_cluster', 'factor'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'ResponseId'. You can override using the `.groups` argument.
## Linear mixed model fit by REML ['lmerMod']
## Formula: response ~ dev_factor_cluster * factor + (1 + dev_factor_cluster +  
##     factor | ResponseId) + (1 | dev_factor) + (1 | capacity)
##    Data: d3_mech_ratings
## Control: lmerControl(optimizer = "bobyqa")
## 
## REML criterion at convergence: 84145.5
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -4.3297 -0.6590 -0.0029  0.6601  3.3378 
## 
## Random effects:
##  Groups     Name                     Variance Std.Dev. Corr                   
##  ResponseId (Intercept)              0.80191  0.8955                          
##             dev_factor_clusterext_gm 0.09652  0.3107   -0.05                  
##             factorbod_gm             0.39914  0.6318    0.44 -0.14            
##             factorsoc_gm             0.16402  0.4050   -0.26  0.11 -0.73      
##             factorcog_gm             0.23591  0.4857   -0.61 -0.03 -0.77  0.49
##  dev_factor (Intercept)              0.46449  0.6815                          
##  capacity   (Intercept)              0.09151  0.3025                          
##  Residual                            2.56034  1.6001                          
## Number of obs: 21672, groups:  ResponseId, 301; dev_factor, 9; capacity, 8
## 
## Fixed effects:
##                                       Estimate Std. Error t value
## (Intercept)                            3.09644    0.25783  12.009
## dev_factor_clusterext_gm               0.28487    0.22955   1.241
## factorbod_gm                          -0.58979    0.18974  -3.108
## factorsoc_gm                           0.58616    0.18767   3.123
## factorcog_gm                           0.24189    0.18831   1.285
## dev_factor_clusterext_gm:factorbod_gm -1.11876    0.01894 -59.058
## dev_factor_clusterext_gm:factorsoc_gm  0.36077    0.01894  19.044
## dev_factor_clusterext_gm:factorcog_gm  0.88278    0.01894  46.601
## 
## Correlation of Fixed Effects:
##                           (Intr) dv_f__ fctrb_ fctrs_ fctrc_
## dv_fctr_cl_               -0.099                            
## factorbd_gm                0.017 -0.002                     
## factorsc_gm               -0.006  0.001 -0.342              
## factorcg_gm               -0.018  0.000 -0.346 -0.318       
## dv_fctr_clstrxt_gm:fctrb_  0.000  0.000 -0.011  0.004  0.004
## dv_fctr_clstrxt_gm:fctrs_  0.000  0.000  0.004 -0.011  0.004
## dv_fctr_clstrxt_gm:fctrc_  0.000  0.000  0.004  0.004 -0.011
##                           dv_fctr_clstrxt_gm:fctrb_ dv_fctr_clstrxt_gm:fctrs_
## dv_fctr_cl_                                                                  
## factorbd_gm                                                                  
## factorsc_gm                                                                  
## factorcg_gm                                                                  
## dv_fctr_clstrxt_gm:fctrb_                                                    
## dv_fctr_clstrxt_gm:fctrs_ -0.333                                             
## dv_fctr_clstrxt_gm:fctrc_ -0.333                    -0.333
## Linear mixed model fit by REML ['lmerMod']
## Formula: 
## response ~ dev_factor_cluster + (1 + dev_factor_cluster | ResponseId) +  
##     (1 | dev_factor) + (1 | capacity)
##    Data: d3_mech_ratings %>% filter(factor == "Bodily sensations")
## Control: lmerControl(optimizer = "bobyqa")
## 
## REML criterion at convergence: 20410.1
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -5.2099 -0.6107 -0.0514  0.5765  3.7935 
## 
## Random effects:
##  Groups     Name                     Variance Std.Dev. Corr
##  ResponseId (Intercept)              1.638945 1.28021      
##             dev_factor_clusterext_gm 0.233138 0.48284  0.60
##  dev_factor (Intercept)              0.928326 0.96350      
##  capacity   (Intercept)              0.001675 0.04093      
##  Residual                            2.055307 1.43363      
## Number of obs: 5418, groups:  ResponseId, 301; dev_factor, 9; capacity, 2
## 
## Fixed effects:
##                          Estimate Std. Error t value
## (Intercept)                2.5066     0.3333   7.520
## dev_factor_clusterext_gm  -0.8339     0.3250  -2.566
## 
## Correlation of Fixed Effects:
##             (Intr)
## dv_fctr_cl_ -0.096
## Linear mixed model fit by REML ['lmerMod']
## Formula: 
## response ~ dev_factor_cluster + (1 + dev_factor_cluster | ResponseId) +  
##     (1 | dev_factor) + (1 | capacity)
##    Data: d3_mech_ratings %>% filter(factor == "Negative affect")
## Control: lmerControl(optimizer = "bobyqa")
## 
## REML criterion at convergence: 21649.8
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -3.04361 -0.68969 -0.03827  0.70000  2.80155 
## 
## Random effects:
##  Groups     Name                     Variance  Std.Dev. Corr
##  ResponseId (Intercept)              1.1151187 1.05599      
##             dev_factor_clusterext_gm 0.2255416 0.47491  0.36
##  dev_factor (Intercept)              0.7504263 0.86627      
##  capacity   (Intercept)              0.0007574 0.02752      
##  Residual                            2.6733052 1.63502      
## Number of obs: 5418, groups:  ResponseId, 301; dev_factor, 9; capacity, 2
## 
## Fixed effects:
##                          Estimate Std. Error t value
## (Intercept)                2.8582     0.2983   9.580
## dev_factor_clusterext_gm   0.1601     0.2927   0.547
## 
## Correlation of Fixed Effects:
##             (Intr)
## dv_fctr_cl_ -0.101
## Linear mixed model fit by REML ['lmerMod']
## Formula: 
## response ~ dev_factor_cluster + (1 + dev_factor_cluster | ResponseId) +  
##     (1 | dev_factor) + (1 | capacity)
##    Data: d3_mech_ratings %>% filter(factor == "Social connection")
## Control: lmerControl(optimizer = "bobyqa")
## 
## REML criterion at convergence: 20877.7
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -3.6315 -0.5963  0.0956  0.6517  3.1847 
## 
## Random effects:
##  Groups     Name                     Variance Std.Dev. Corr 
##  ResponseId (Intercept)              0.8011   0.8950        
##             dev_factor_clusterext_gm 0.1719   0.4146   -0.16
##  dev_factor (Intercept)              0.6350   0.7969        
##  capacity   (Intercept)              0.3074   0.5544        
##  Residual                            2.3440   1.5310        
## Number of obs: 5418, groups:  ResponseId, 301; dev_factor, 9; capacity, 2
## 
## Fixed effects:
##                          Estimate Std. Error t value
## (Intercept)                3.6826     0.4777   7.709
## dev_factor_clusterext_gm   0.6456     0.2692   2.399
## 
## Correlation of Fixed Effects:
##             (Intr)
## dv_fctr_cl_ -0.064
## Linear mixed model fit by REML ['lmerMod']
## Formula: 
## response ~ dev_factor_cluster + (1 + dev_factor_cluster | ResponseId) +  
##     (1 | dev_factor) + (1 | capacity)
##    Data: d3_mech_ratings %>% filter(factor == "Cognition and control")
## Control: lmerControl(optimizer = "bobyqa")
## 
## REML criterion at convergence: 19561.1
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -3.8585 -0.5546  0.0667  0.5785  3.6821 
## 
## Random effects:
##  Groups     Name                     Variance Std.Dev. Corr 
##  ResponseId (Intercept)              0.57475  0.7581        
##             dev_factor_clusterext_gm 0.40527  0.6366   -0.26
##  dev_factor (Intercept)              0.42184  0.6495        
##  capacity   (Intercept)              0.05676  0.2383        
##  Residual                            1.76819  1.3297        
## Number of obs: 5418, groups:  ResponseId, 301; dev_factor, 9; capacity, 2
## 
## Fixed effects:
##                          Estimate Std. Error t value
## (Intercept)                3.3383     0.2794  11.947
## dev_factor_clusterext_gm   1.1676     0.2217   5.268
## 
## Correlation of Fixed Effects:
##             (Intr)
## dv_fctr_cl_ -0.093
## `summarise()` has grouped output by 'ResponseId', 'dev_factor_cluster', 'factor'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'ResponseId', 'dev_factor_cluster'. You can override using the `.groups` argument.

“Other” responses

Developmental mechanisms: Selection of “most important”

## Generalized linear mixed model fit by maximum likelihood (Laplace
##   Approximation) [glmerMod]
##  Family: binomial  ( logit )
## Formula: extrinsic ~ factor + (1 | ResponseId) + (1 | capacity)
##    Data: d3_mech_choice %>% mutate(extrinsic = case_when(dev_factor_cluster ==  
##     "extrinsic" ~ 1, dev_factor_cluster == "intrinsic" ~ 0, is.na(dev_factor_cluster) ~  
##     NA_real_, TRUE ~ NA_real_))
## Control: glmerControl(optimizer = "bobyqa")
## 
##      AIC      BIC   logLik deviance df.resid 
##   1578.9   1612.3   -783.5   1566.9     1916 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -5.0902 -0.3463 -0.1044  0.3877 13.5689 
## 
## Random effects:
##  Groups     Name        Variance Std.Dev.
##  ResponseId (Intercept) 2.2531   1.5010  
##  capacity   (Intercept) 0.4484   0.6697  
## Number of obs: 1922, groups:  ResponseId, 301; capacity, 8
## 
## Fixed effects:
##              Estimate Std. Error z value Pr(>|z|)    
## (Intercept)   -0.6927     0.2677  -2.588  0.00966 ** 
## factorbod_gm  -3.7301     0.4711  -7.917 2.43e-15 ***
## factorsoc_gm   1.2286     0.4298   2.858  0.00426 ** 
## factorcog_gm   2.6981     0.4426   6.096 1.09e-09 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##             (Intr) fctrb_ fctrs_
## factorbd_gm  0.088              
## factorsc_gm -0.040 -0.362       
## factorcg_gm -0.025 -0.389 -0.290
## Generalized linear mixed model fit by maximum likelihood (Laplace
##   Approximation) [glmerMod]
##  Family: binomial  ( logit )
## Formula: extrinsic ~ 1 + (1 | ResponseId) + (1 | capacity)
##    Data: d3_mech_choice %>% filter(factor == "Bodily sensations") %>%  
##     mutate(extrinsic = case_when(dev_factor_cluster == "extrinsic" ~  
##         1, dev_factor_cluster == "intrinsic" ~ 0, is.na(dev_factor_cluster) ~  
##         NA_real_, TRUE ~ NA_real_))
## Control: glmerControl(optimizer = "bobyqa")
## 
##      AIC      BIC   logLik deviance df.resid 
##    139.1    152.2    -66.5    133.1      583 
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -0.93243 -0.01169 -0.01051 -0.01046  1.19891 
## 
## Random effects:
##  Groups     Name        Variance Std.Dev.
##  ResponseId (Intercept) 70.12434 8.3740  
##  capacity   (Intercept)  0.06855 0.2618  
## Number of obs: 586, groups:  ResponseId, 300; capacity, 2
## 
## Fixed effects:
##             Estimate Std. Error z value Pr(>|z|)    
## (Intercept)  -9.0691     0.7369  -12.31   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Generalized linear mixed model fit by maximum likelihood (Laplace
##   Approximation) [glmerMod]
##  Family: binomial  ( logit )
## Formula: extrinsic ~ 1 + (1 | ResponseId) + (1 | capacity)
##    Data: 
## d3_mech_choice %>% filter(factor == "Negative affect") %>% mutate(extrinsic = case_when(dev_factor_cluster ==  
##     "extrinsic" ~ 1, dev_factor_cluster == "intrinsic" ~ 0, is.na(dev_factor_cluster) ~  
##     NA_real_, TRUE ~ NA_real_))
## Control: glmerControl(optimizer = "bobyqa")
## 
##      AIC      BIC   logLik deviance df.resid 
##    572.4    585.0   -283.2    566.4      479 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -1.1498 -0.5462 -0.3689  0.7856  1.8310 
## 
## Random effects:
##  Groups     Name        Variance Std.Dev.
##  ResponseId (Intercept) 1.1262   1.0612  
##  capacity   (Intercept) 0.7454   0.8634  
## Number of obs: 482, groups:  ResponseId, 288; capacity, 2
## 
## Fixed effects:
##             Estimate Std. Error z value Pr(>|z|)
## (Intercept)  -0.8027     0.6266  -1.281      0.2
## Generalized linear mixed model fit by maximum likelihood (Laplace
##   Approximation) [glmerMod]
##  Family: binomial  ( logit )
## Formula: extrinsic ~ 1 + (1 | ResponseId) + (1 | capacity)
##    Data: d3_mech_choice %>% filter(factor == "Social connection") %>%  
##     mutate(extrinsic = case_when(dev_factor_cluster == "extrinsic" ~  
##         1, dev_factor_cluster == "intrinsic" ~ 0, is.na(dev_factor_cluster) ~  
##         NA_real_, TRUE ~ NA_real_))
## Control: glmerControl(optimizer = "bobyqa")
## 
##      AIC      BIC   logLik deviance df.resid 
##    579.6    592.0   -286.8    573.6      462 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -1.6698 -0.7710  0.3616  0.5989  1.2970 
## 
## Random effects:
##  Groups     Name        Variance Std.Dev.
##  ResponseId (Intercept) 1.6682   1.2916  
##  capacity   (Intercept) 0.8469   0.9203  
## Number of obs: 465, groups:  ResponseId, 279; capacity, 2
## 
## Fixed effects:
##             Estimate Std. Error z value Pr(>|z|)
## (Intercept)   0.5217     0.6665   0.783    0.434
## boundary (singular) fit: see ?isSingular
## Generalized linear mixed model fit by maximum likelihood (Laplace
##   Approximation) [glmerMod]
##  Family: binomial  ( logit )
## Formula: extrinsic ~ 1 + (1 | ResponseId) + (1 | capacity)
##    Data: d3_mech_choice %>% filter(factor == "Cognition and control") %>%  
##     mutate(extrinsic = case_when(dev_factor_cluster == "extrinsic" ~  
##         1, dev_factor_cluster == "intrinsic" ~ 0, is.na(dev_factor_cluster) ~  
##         NA_real_, TRUE ~ NA_real_))
## Control: glmerControl(optimizer = "bobyqa")
## 
##      AIC      BIC   logLik deviance df.resid 
##    299.9    311.8   -146.9    293.9      386 
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -1.05415  0.01476  0.01476  0.01500  0.94864 
## 
## Random effects:
##  Groups     Name        Variance Std.Dev.
##  ResponseId (Intercept) 156.8    12.52   
##  capacity   (Intercept)   0.0     0.00   
## Number of obs: 389, groups:  ResponseId, 251; capacity, 2
## 
## Fixed effects:
##             Estimate Std. Error z value Pr(>|z|)    
## (Intercept)   8.3639     0.8337   10.03   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## optimizer (bobyqa) convergence code: 0 (OK)
## boundary (singular) fit: see ?isSingular
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XX

XX

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Perceived importance of various mechanisms in the development of four domains of mental life (Study 3); see main text for the full text of each mechanism. Panel A shows ratings for each developmental mechanism and both of the capacities within each domain; Panel B shows mean ratings for intrinsic vs. extrinsic mechanisms for each domain of capacities; and Panel C shows the percentage of trials on which participants selected intrinsic vs. extrinsic mechanisms as the 'most important' driver of development. Lighter points and lines represent individual participants’ responses, black points correspond to mean scores across the sample, and error bars are bootstrapped 95% confidence intervals. The dotted red line at the midpoint of the response scale in Panels A and B is intended to aid visual comparison across domains.

Perceived importance of various mechanisms in the development of four domains of mental life (Study 3); see main text for the full text of each mechanism. Panel A shows ratings for each developmental mechanism and both of the capacities within each domain; Panel B shows mean ratings for intrinsic vs. extrinsic mechanisms for each domain of capacities; and Panel C shows the percentage of trials on which participants selected intrinsic vs. extrinsic mechanisms as the ‘most important’ driver of development. Lighter points and lines represent individual participants’ responses, black points correspond to mean scores across the sample, and error bars are bootstrapped 95% confidence intervals. The dotted red line at the midpoint of the response scale in Panels A and B is intended to aid visual comparison across domains.

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## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <99>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <98>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <99>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <98>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
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## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <99>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <98>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
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## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <99>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <98>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <99>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
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## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <98>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <99>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <98>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <99>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <98>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <99>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <98>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <99>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <98>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <99>
## Warning in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <98>
## Warning in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <99>
## Warning in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <98>
## Warning in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <e2>
## Warning in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <80>
## Warning in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :
## conversion failure on '‘preprogrammed’' in 'mbcsToSbcs': dot substituted for
## <99>

“Other” responses

References